Knowledge catalogue
arXiv:2604.20819v1 Announce Type: new Abstract: The scalability of long-context large language models is fundamentally limited by the quadratic memory cost of exact self-attention, which often leads t
arXiv:2604.18616v1 Announce Type: cross Abstract: LLM-based coding agents can generate functionally correct GPU kernels, yet their performance remains far below hand-optimized libraries on critical co
NVIDIA AI and accelerated computing are advancing sustainability, climate science and energy efficiency through five key applications. These include RecycleOS, an AI and robotics solution that helps r
arXiv:2412.00069v3 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) has garnered significant attention for its ability to scale up neural networks while utilizing the same or even fewer
arXiv:2604.17808v1 Announce Type: cross Abstract: Zero-knowledge proof (ZKP) provers remain costly because multi-scalar multiplication (MSM) and number-theoretic transforms (NTTs) dominate runtime as
arXiv:2602.11092v2 Announce Type: replace Abstract: Identifying where quantum models may offer practical benefits in near term quantum machine learning (QML) requires moving beyond isolated algorithmi
arXiv:2510.04008v5 Announce Type: replace Abstract: Softmax Attention has a quadratic time complexity in sequence length, which becomes prohibitive to run at long contexts, even with highly optimized
arXiv:2604.16715v1 Announce Type: cross Abstract: Graph foundation models have demonstrated remarkable adaptability across diverse downstream tasks through large-scale pretraining on graphs. However,
arXiv:2604.18067v1 Announce Type: new Abstract: The miniaturisation of neural processing units (NPUs) and other low-power accelerators has enabled their integration into microcontroller-scale wearable
arXiv:2604.17050v1 Announce Type: new Abstract: With the rapid development of embodied intelligence, robotics education faces a dual challenge: high computational barriers and cumbersome environment c
arXiv:2604.15769v1 Announce Type: cross Abstract: Spiking transformers achieve competitive accuracy with conventional transformers while offering 38-57imes energy efficiency on neuromorphic hardware,
arXiv:2603.03188v2 Announce Type: replace-cross Abstract: We introduce a novel framework for uncertainty quantification in clustering that combines martingale posterior distributions with density-base
We’re launching Kimi K2.6 on Fireworks as a Day-0 launch partner! K2.5 was the base for standout models like @Cursor’s Composer 2 and was the most popular model on our training platform. K2.6 on Firew
arXiv:2604.13048v1 Announce Type: cross Abstract: Modern cloud-native platforms expose thousands of time series metrics through systems like Prometheus, yet formulating correct queries in domain-speci
arXiv:2511.19204v3 Announce Type: replace Abstract: We present a sampling-based model predictive control (MPC) framework that enables emergent locomotion without relying on handcrafted gait patterns o
Heterogeneous computing, which combines multiple types of GPUs and processors, is becoming standard in enterprise environments to handle diverse workloads more efficiently than traditional homogeneous
This Reddit post from r/ollama discusses a user's experience running Cline (an AI coding agent) with Ollama on a high-end local hardware setup consisting of an NVIDIA RTX 4090 with 24GB VRAM and an In
This Reddit thread from r/StableDiffusion discusses a performance issue where Roop Unleashed version 4.3.1 — a face-swapping tool commonly used alongside Stable Diffusion — fails to fully utilize the
A Reddit post from r/ollama in which a user shares their experience running a 31B parameter model locally using Ollama, reflecting on the surprisingly demanding hardware and infrastructure requirement
🆕 The Full Story of Notion AI https://latent.space/p/notion We're so excited to chat with @simonlast and @sarahmsachs about Notion's 'Token Town' - the crack team of AI Engineers and Model Behavior En
arXiv:2604.11615v1 Announce Type: cross Abstract: Matrix extensions have emerged as an essential feature in modern CPUs to address the surging demands of AI workloads. However, existing designs often
arXiv:2604.10170v1 Announce Type: cross Abstract: The growing complexity of visuomotor policies poses significant challenges for deployment with heterogeneous robotic hardware constraints. However, mo
arXiv:2604.10539v1 Announce Type: cross Abstract: Key-Value (KV) cache plays a crucial role in accelerating inference in large language models (LLMs) by storing intermediate attention states and avoid
NVIDIA Ising is the world's first family of open-source quantum AI models, designed to help researchers and enterprises build quantum processors capable of running useful applications. The family span
arXiv:2604.11625v1 Announce Type: cross Abstract: Neural operators have emerged as powerful surrogates for partial differential equation (PDE) solvers, yet they are typically trained as monolithic mod
arXiv:2604.10180v1 Announce Type: cross Abstract: Disaggregation maps parts of an AI workload to different types of GPUs, offering a path to utilize modern heterogeneous GPU clusters. However, existin
arXiv:2604.09943v1 Announce Type: new Abstract: Reservoir computing (RC) is a computational framework known for its training efficiency, making it ideal for physical hardware implementations. However,
This Reddit thread from r/ollama discusses community recommendations for purchasing or renting GPU servers to run Ollama and local LLMs. It likely covers options ranging from dedicated GPU server prov
Soumith Chintala shared a post highlighting that $200 per month is sufficient to rent access to an NVIDIA H100 GPU for approximately 6 hours every workday, making high-end AI compute more accessible t
"**AI Engineer Europe (London) — Conference Recap**
In freeskiing and snowboarding, traditional video replay shows you what happened during a complex aerial maneuver, but it fails to explain the physics of how it was possible. At the speed of the sport
Together Computer (Together AI) participated in HumanX 2026, a major AI conference held April 6–9 in San Francisco, where they hosted activations including custom comics, branded hats, and a happy ...
Training LLMs requires periodic checkpoints — full snapshots of model weights, optimizer states, and gradients — whose storage costs can reach $200,000/month for a 405B model on 128 NVIDIA DGX B200...
NVIDIA, Google DeepMind, EMBL-EBI, and Seoul National University collaborated to extend the AlphaFold Protein Structure Database (AFDB) beyond monomeric structures to proteome-scale quaternary stru...
NVIDIA's open-source project **Slinky** (developed by SchedMD, now part of NVIDIA) enables organizations to run full Slurm clusters directly on Kubernetes infrastructure by managing the complete li...
NVIDIA has introduced a modular, library-based architecture for Omniverse, exposing core components—RTX rendering, PhysX-based simulation, and data storage pipelines—as standalone, headless-first C...
Vultr has upgraded its Identity and Access Management (IAM) framework by replacing legacy ACLs with fine-grained, policy-driven access controls, enabling organizations to assign roles, manage permi...
I was unable to directly access the YouTube video at the provided URL, and my search did not return results specifically identifying that video's content. YouTube videos cannot be fetched or read a...
arXiv:2608.10720v1 Announce Type: new Abstract: Omni-modal dialogue models can understand multimodal inputs and synthesize spoken replies, yet their responses remain visually disembodied. We introduce
arXiv:2608.10317v1 Announce Type: new Abstract: We present TAR (Traffic Anomaly Reasoning) and TAR-Bench datasets, resources for training and evaluating video-language models beyond anomaly detection.
arXiv:2608.10103v1 Announce Type: cross Abstract: High-performance Tensor Core kernels rely on a low-level PTX pipeline built from asynchronous data movement with cp.async, warp-level matrix loads wit
A full‑stack observability framework for NVIDIA AI factories links telemetry from compute, networking, storage, orchestration and application layers using specialized tools (DCGM, NVSM, UFM, NetQ, NMX
arXiv:2510.12947v3 Announce Type: replace-cross Abstract: Voice activity detection (VAD) serves as an early gate in voice-assistant pipelines for smart devices. Because conventional VADs respond to sp
IBM Corp. will provide infrastructure to artificial intelligence startup Together AI Inc. as part of a 240 million deal announced today. The partnership comes a few weeks after the latter company rais
First private neocloud to execute an investment-grade-rated financing in the term loan B market, further broadening the investor base for AI infrastructure financing. Facility supports the purchase an
arXiv:2608.10323v1 Announce Type: new Abstract: Competitive artificial-life systems can rank trained controllers differently under training and ecological evaluation. We present Neuroevolution Arena,
We announced partnerships with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to establish independent financing platforms designed to mobilize over $500 billion of third-party capit
arXiv:2608.10402v1 Announce Type: new Abstract: Reinforcement learning (RL) for large language models is moving toward multi-turn agentic workloads, where rollout tasks repeatedly pause for external e
Running large language model inference at scale forces a KV cache trade-off: oversized GPU instances or slow time-to-first-token. This post builds a tiered KV cache on Amazon SageMaker HyperPod that e
arXiv:2504.11500v3 Announce Type: replace-cross Abstract: Transit Origin-Destination (OD) data are fundamental for optimizing public transit services, yet current collection methods, such as manual su
arXiv:2608.07575v1 Announce Type: new Abstract: Confocal microscopy of optically cleared and swelled tissue resolves complex biological structures in 3D, but such acquisitions are highly anisotropic:
Ben Thompson / Stratechery: Big Tech's AI boom echoes the 1870s railroad buildout, and Nvidia shifting risk to institutional capital may expose investors if AI revenues fail to materialize — On Januar
arXiv:2608.09444v1 Announce Type: cross Abstract: A main promise of looped language models (LMs) is depth-adaptive inference. By iterating a block of shared layers a variable number of times, the mode
arXiv:2603.14700v2 Announce Type: replace-cross Abstract: Machine learning interatomic potentials (MLIPs) have become widely used tools in atomistic simulations. For much of the history of this field,
arXiv:2608.08559v1 Announce Type: cross Abstract: Differentiable simulation is a key component in learning, control, and inverse problems, where gradients through nonlinear implicit solvers are requir
arXiv:2608.07964v1 Announce Type: cross Abstract: Load Balancing has emerged as a critical problem in expert-parallel distributed inference of Mixture-of-Experts (MoE) models. As routing distributions
arXiv:2608.08531v1 Announce Type: new Abstract: Deep learning-driven representations such as neural radiance fields (NeRFs) and 3D Gaussian splatting (3DGS) have revolutionized the field of dynamic 3D
arXiv:2608.08522v1 Announce Type: new Abstract: Event-based vision is becoming an increasingly important sensing paradigm for robotics, yet its adoption remains limited by sensor availability and the
arXiv:2608.09450v1 Announce Type: new Abstract: Betting-based sequential tests and Blackwell approachability are linked by a rate-explicit reduction through support-function residuals. For a compact c
arXiv:2608.07707v1 Announce Type: new Abstract: Computing distances between sets is essential in robotic motion planning and control, where differentiable gradients enable real-time optimization. The